The invention will now be described, by way of example, with reference to the accompanying drawings, in which:
The present invention is a system and method for quantifying a sound into dynamic pitch-based graphs by recording a sound, such as musical notes, and then provides a pitch detection algorithm that quantifies the pitch of the sound by generating a graphical representation of variances and durations in the pitch through artistic, data-driven formats in real time.
Those skilled in the art will recognize that pitch, in the musical sense, is the degree of height or depth of a tone or of sound, depending upon the relative rapidity of the vibrations by which it is produced. Often, pitch is a perceptual property that allows the ordering of sounds on a frequency-related scale. Pitches are compared as “higher” and “lower” in the sense associated with musical melodies, which require sound whose frequency is clear and stable enough to distinguish from noise. Pitch is a major auditory attribute of musical tones, along with duration, loudness, and timbre. In music the pitch of a note means how high or low a note is. The pitch of a note can be measured in units of Hertz.
Typically, in music, a note is a unit of fixed pitch that has been given a name, or the graphic representation of that pitch in a notation system, and often specifies a duration of time. A scale is an ascending or descending series of notes or pitches. Scales are described in many types such as tonal, modal, diatonic, derived or synthetic, and by the number of tones included. In the chromatic scale there are twelve pitches, and in the English language, these pitches are traditionally assigned the following primary letter names: A, B, C, D, E, F, and G. Modifiers are given to the letter names to complete the remaining five pitches. The two main modifiers are sharps and flats, and which respectively raise or lower the pitch of a note by a semitone.
In many instances, the basic ability required of a student of music is to produce and sustain a musical tone of defined pitch. This task is easy on an instrument like a piano which mechanically quantizes pitch. A singer, however, must dynamically adjust their vocal muscles to control pitch based on their aural perceptions. Similarly, a violinist must adjust their bowing and fingering based on their aural perceptions.
Typically, in music instruction, a student's aural perceptions are typically developed through collaboration with a music teacher who points out, by verbal comment and audible example, the pitch and timing errors of the student. Teaching musical skills is complicated by the fact that sound, unlike paintings, cannot directly be seen and only exist when played. Audio tape recorders allow a student to review their performance, but do not provide any analysis. Furthermore, teaching proper pitch requires minute observations of variances in the pitch.
It is known that the Fourier transform is a mathematical transformation employed to transform signals between time (or spatial) domain and frequency domain. This can have many applications in physics and engineering. For example, an audio signal from an instrument can be converted into an oscillating pitch frequency. This helps partially to quantify the sound. This pitch frequency is, however, insufficient for analyzing whether the pitch is correct or off key. Furthermore, Fourier Transformations do not produce a good speed versus accuracy trade off. Also, Fourier transformation by itself cannot determine pitch frequency. Another algorithm layered on top of the Fourier transformation is needed for this function. If the windows were long enough, the Fourier transformation could, however, quantify the sound to a reasonable degree.
In view of the foregoing, it is clear that these traditional techniques are not perfect and leave room for more optimal approaches.